Invention Grant
- Patent Title: Complex evolution recurrent neural networks
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Application No.: US16251430Application Date: 2019-01-18
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Publication No.: US10529320B2Publication Date: 2020-01-07
- Inventor: Izhak Shafran , Thomas E. Bagby , Russell John Wyatt Skerry-Ryan
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Fish & Richardson P.C.
- Main IPC: G10L15/16
- IPC: G10L15/16 ; G10L19/02 ; G10L15/02 ; G10H1/00 ; G06N3/02 ; G10L17/18 ; G10L25/30

Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speech recognition using complex evolution recurrent neural networks. In some implementations, audio data indicating acoustic characteristics of an utterance is received. A first vector sequence comprising audio features determined from the audio data is generated. A second vector sequence is generated, as output of a first recurrent neural network in response to receiving the first vector sequence as input, where the first recurrent neural network has a transition matrix that implements a cascade of linear operators comprising (i) first linear operators that are complex-valued and unitary, and (ii) one or more second linear operators that are non-unitary. An output vector sequence of a second recurrent neural network is generated. A transcription for the utterance is generated based on the output vector sequence generated by the second recurrent neural network. The transcription for the utterance is provided.
Public/Granted literature
- US20190156819A1 COMPLEX EVOLUTION RECURRENT NEURAL NETWORKS Public/Granted day:2019-05-23
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